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- Delft University of Technology (TU Delft)
- NIOZ Royal Netherlands Institute for Sea Research
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- Delft University of Technology (TU Delft); Published yesterday
- Erasmus MC (University Medical Center Rotterdam)
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Field
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optimisation of monitoring density for trend detection and model validation; comparison of ground-based measurement data with RIVM dispersion models and satellite observations; refinement of regional emission
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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into real-world battery applications? Do you enjoy hands-on laboratory work on-scale, reactor optimisation, and developing sustainable chemical processes with industrial relevance? Are you curious about
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into account the different characteristics of the technologies in play (hydrogen generation plants), their location (integration optimisation at plant and cluster level, sector coupling), and their integration
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synthesis, mu-analysis and model-predictive control Experience in model identification, validation and uncertainty quantification based on experimental results Expert proficiency in the use of MATLAB/Simulink
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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are also encouraged to apply. As a postdoctoral researcher, you will perform experimental work with a Deep-UV Raman spectroscopy setup, measuring representative plastic waste samples and optimising
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. Skilled in MATLAB and Python. Experience with C++ and GPU programming (CUDA) is an advantage. Ability to work in a team, communicate effectively, coordinate multidisciplinary collaborations, and manage
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(ideally in Fortran). Experience with parallelisation and Linux clusters is an advantage. You have a demonstrated ability to work with scripting software (e.g. Phyton, Matlab, R) for visualisation and
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to optimise beach clean-ups and thereby prevent these macroplastics from fragmenting into large numbers of microplastics. As a postdoctoral researcher, you will use the Parcels-code.org Lagrangian framework